A MeasureCamp presentation I didn't get time to cover which explains how we used some Google Analytics hacks to analyse e-commerce Returns Management System trends.

1. Returns Management
System hacking
Matt Clarke, @techpad
Sunday, 17 February 13

2. The problem...
• We promised customers we’d handle their
return in 7-10 days.
• We suspected that sometimes returns
didn’t get handled within this time, but our
existing RMS couldn’t tell us.
• When returns handling was slow, call
volume went up, so did email queries. This
annoyed customer services and customers.
Sunday, 17 February 13

3. Step 1: Track emails
• Before we started on a
major rebuild of the
RMS, we added event
tracking to the form
used to categorise
customer service emails
from the site.
• We do a similar thing
with complaints analysis
(there’s a post on that
on my blog).
Sunday, 17 February 13

4. Step 2: Monitor emails
• I built a dashboard to
provide an overview of
emails received.
• I used the API to report
on increases in returns
emails/proportion, which
might indicate a failure
to meet customer
promise.
Sunday, 17 February 13

5. Step 3: Dig deeper
• I spent three months
writing an MSc project
to further investigate the
problem, and proposed a
solution to tackle it.
• The proposed solution
used GA, among other
things...
Sunday, 17 February 13

6. Step 4: Re-build the RMS
• We rebuilt the RMS to
tackle the issues the
business was facing, as
well as those that
impacted customers.
• We added a metrics
system so we could
record which returns
were pending, due today,
late etc, and help staff
prioritise and hit KPIs.
Sunday, 17 February 13

7. Step 5: Plan event tracking
• I made a spreadsheet of
events. There were lots...
• Why GA? Using GA
would mean I could
analyse and report on
the data much more
easily than I could if I
had to write SQL
queries to pull the data
out of the RMS.
Sunday, 17 February 13

8. Step 6: Sent events in PHP-GA
• There were too many
events to send using the
client-side code, so I
used PHP-GA, which
allows you to bypass the
token bucket algorithm.
• Primary keys in the
events allow related
events to be re-joined in
the API.
Sunday, 17 February 13

9. Step 7: Set up reporting
• The default Google
Analytics dashboards
were too limited to be
of use for this problem.
• So, we’re using Google
Drive and the Google
Analytics Core
Reporting API “magic
script” to create detailed
reports.
Sunday, 17 February 13

10. We can now answer these
questions on returns
• What percentage of returns are handled on-time?
• What is the average time to handle returns of
different types - replacement, exchange, refund?
• How many returns are unscheduled arrivals?
• What are the return rates for different items, and
why are they being returned?
• What proportion of faulty goods are non-faulty?
• How much working capital is tied up in returns?
Sunday, 17 February 13